The process of planning for an equitable health care system and for an optimal allocation, organization, and location of resources requires an initial step of the delineation of population groups. Already some HSA's have begun defining population groups and/or service areas for planning purposes, yet the appropriateness of the models being used has not been evaluated. Demand for health care services can effectively be projected only when population factors and local variations in health care delivery practices are adequately taken into account. Health information about sub-regional populations can provide a strong basis not only for studies of levels of utilization of and access to services, but also studies of utilization of manpower and facilities, and associated costs. It can also support system demand projections, analysis of the impact of system changes, quality assessment, and policy research. Health services planning in this country has traditionally focused on expansion or contraction of services in existing health care facilities, with some emphasis on new facilities. This institutional or facility based viewpoint has been reinforced by the mandates and functions of the federally sponsored health planning agencies. An alternative population based viewpoint to health services planning would reflect a primary concern for the needs of and services to be provided to population groups. As the facility based viewpoint is the dominant one, the associated models for delineation of population groups have been developed along those lines; Administrative methods, Normative methods (e.g., Gravity Models and Travel Time Minimization Models), and Empirical methods (e.g., Market Penetration Models) all reflect this. In support of the latter viewpoint, a Population Based Model using cluster analysis, and based on the spatial behavior (utilization patterns) of the population, will be developed in this research. Following that, all the models will be applied to the Central Maryland area, covering a three-year period. The relative degree of validity of the models will then be assessed using three types of construct validity measures, and their relative degree of reliability will be assessed using stability and homogeneity measures.